{"title":"RAM3S教给我们什么","authors":"Ilaria Bartolini, M. Patella","doi":"10.1145/3428757.3429098","DOIUrl":null,"url":null,"abstract":"RAM3S (Real-time Analysis of Massive MultiMedia Streams) is a framework that acts as a middleware software layer between multimedia stream analysis techniques and Big Data streaming platforms, so as to facilitate the implementation of the former on top of the latter. Indeed, the use of Big Data platforms can give way to the efficient management and analysis of large data amounts, but they require the user to concentrate on issues related to distributed computing, since their services are often too raw. The use of RAM3S greatly simplifies deploying non-parallel techniques to platforms like Apache Storm or Apache Flink, a fact that is demonstrated by the four different use cases we describe here. We detail the lessons we learned from exploiting RAM3S to implement the detailed use cases.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rammed, or What RAM3S Taught Us\",\"authors\":\"Ilaria Bartolini, M. Patella\",\"doi\":\"10.1145/3428757.3429098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"RAM3S (Real-time Analysis of Massive MultiMedia Streams) is a framework that acts as a middleware software layer between multimedia stream analysis techniques and Big Data streaming platforms, so as to facilitate the implementation of the former on top of the latter. Indeed, the use of Big Data platforms can give way to the efficient management and analysis of large data amounts, but they require the user to concentrate on issues related to distributed computing, since their services are often too raw. The use of RAM3S greatly simplifies deploying non-parallel techniques to platforms like Apache Storm or Apache Flink, a fact that is demonstrated by the four different use cases we describe here. We detail the lessons we learned from exploiting RAM3S to implement the detailed use cases.\",\"PeriodicalId\":212557,\"journal\":{\"name\":\"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3428757.3429098\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3428757.3429098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
RAM3S (Real-time Analysis of Massive MultiMedia Streams)是一个介于多媒体流分析技术和大数据流平台之间的中间件软件层框架,便于大数据流分析技术在大数据流平台之上实现。的确,大数据平台的使用可以让位于对大量数据的有效管理和分析,但它们要求用户专注于与分布式计算相关的问题,因为它们的服务往往过于原始。RAM3S的使用极大地简化了在Apache Storm或Apache Flink等平台上部署非并行技术,我们在这里描述的四个不同用例证明了这一点。我们详细介绍了利用RAM3S实现详细用例的经验教训。
RAM3S (Real-time Analysis of Massive MultiMedia Streams) is a framework that acts as a middleware software layer between multimedia stream analysis techniques and Big Data streaming platforms, so as to facilitate the implementation of the former on top of the latter. Indeed, the use of Big Data platforms can give way to the efficient management and analysis of large data amounts, but they require the user to concentrate on issues related to distributed computing, since their services are often too raw. The use of RAM3S greatly simplifies deploying non-parallel techniques to platforms like Apache Storm or Apache Flink, a fact that is demonstrated by the four different use cases we describe here. We detail the lessons we learned from exploiting RAM3S to implement the detailed use cases.